Using Reinforcement Learning To Learn To Play Tic-Tac-ToeAbout a year ago I set myself the goal of writing an algorithm that could learn to play tic-tac-toe. I didn't want to tell the algorithm what the rules of the game are, nor did I want it to try and use some kind of calculation to look ahead at possible ...

The best opening move in a game of tic-tac-toeAs part of a machine learning project, I had to understand tic-tac-toe better, and so I have written an algorithm which a) finds all the possible unique games and b) gathers statistical information about those games. Based on Wikipedia's tic-tac-toe ...

A while ago some colleagues attended a lecture where the presenter introduced the idea that applications may not take full advantage of the multi-core servers which are available today. The idea was that if you have two cores but a process which is running on a single thread, then all the work is done on one single core. Application servers help in this respect, because they handle multiple incoming requests simultaneously, by starting a new thread for each request. So if the server has two cores it can really handle two requests simultaneously, or if it has 6 cores, it can handle 6 requests simultanously.

So multi-core CPUs can help the performance of your server if you have multiple simultaneous requests, which is often the case when your server is running near its limit. But it's not often the case that you want your servers running close to the limit, so you typically scale out, by adding more nodes to your server cluster, which has a similar effect to adding cores to the CPU (you can continue to handle multiple requests simultaneously).

So once you have scaled up by adding more cores, and scaled out by adding more servers, how can you improve performance?

Some processes can be designed to be non-serial, especially in enterprise scenarios. The Wikipedia article on multi-core processors talks about this. Imagine a process which gathers data from multiple systems while preparing the data which it responds with. An example would be a pricing system. Imagine your local zoo offered a web service for purchasing individual tickets, say an entrance ticket, a voucher for some tasty elephant snacks for feeding time, a voucher for their shop for getting gifts before you leave, etc. Now imagine, you as an entrepreneur wanted to open a re-selling business offering packages for such products, so that you could offer a discount (greater sales volume, lower per-item profit).

A perfect way to do this would be to partner with the Zoo and offer a website which integrates with the zoo's web service and sells such packages. You implement your website, but then while doing performance tests, you notice that regardless of load, an average sales is taking 3 seconds to complete. You analyse the system and determine that its the zoo's web service which is the problem - each product quote is taking a full second to get. You talk to the zoo's IT department, and they confirm that this is known, but there is little they can do about it because in the back end they are using complex reservation systems which work out a dynamic market price which is based on supply and demand.

So, you go away and have a think, and remember that your data center has just just installed some servers with flashy new multi-core processors, which are costing you a fortune. Then it hits you! Getting a product quote is an independent task. So while getting quotes for the items in your package, you might as well do it in parallel, at the same time! Hang on now. You implemented your system in Java and the business logic is in EJBs, so there's no chance of spawning new threads, the container won't let you! Except... you implemented it on a shiny new Java EE 6 server! Hooray! Why? Because of the javax.ejb.Asynchronous annotation.

The Javadocs for this annotation state:

Used to mark a method as an asynchronous method or to designate all business methods of a class or interface as asynchronous.

So, what you do, is add this annotation to a business method of your EJB and the container runs it on a new thread. Brilliant! The only minor issue is how to get the result from your asynchronous calls, but that's relatively easy, using the Future<T> class. Consider the following method declaration:

This EJB business method takes a product and purchase ID (effectively a session ID). It gets called by the container on a new thread, which implicitly means that it cannot re-use any existing transactions and must hence be run using a new transaction (see EJB specification, chapter 4.5.3). This method then calls the zoo's web service and when it gets a response, returns the response:

return new AsyncResult(o);

where "o" is an offer - the response from the web service call. The javax.ejb.AsyncResult<T> class is the standard implentation of a Future<T>, and simply wraps the actual object you want to return.

The EJB which started the async calls knows when they have all returned, because it can check the results isDone() method. As soon as the new thread completes, the container sets this method to return true.

So, the net effect is that instead of taking three seconds to get an offer for your package of three items, it only takes one second! A whopping 300% improvement!

The async annotation in the EJB spec is a welcome extension. If also offers the ability to cancel tasks as well as handle exceptions from the async calls (via ExecutionExceptions which wrap the problem). With it however, there are some dangers, as suggested in the Wikipedia article on multi-core processors. The fact that such async methods are forced to start a new transaction can cause problems. However, this is actually an advantage, because we are calling web services! Web services are inherently non-transactional. That means they are committed as soon as you get their response, not as soon as your transaction is committed. So in order to make web services XA (two phase commit) compatible, one normally adds a "commit" method to the web service which the caller must call when all their business logic is complete, or one adds a mechanism for cancelling such transactions.

I have used the new "inner" transaction which the container starts to track the state of these offers / sales. As soon as the web service returns, I write the result to a table in the database with its status "OFFERED", so that I know I have not actually purchased it. Regardless of errors in other calls to the web service, I am guaranteed to have such an entry for each successful web service result, due to the inner transaction. After I get the three offers, the orchestration EJB which called the async bean (which calls the web services), purchases the three offers. After each purchase, I update the status in the database to "BOUGHT", also using an inner transaction (REQUIRES_NEW), so that regardless of any failures in subsequent purchases, the state of individual purchases is known. Why go to this effort? Well, I have a business rule: my packages are sold as complete packages, or not at all! So if any single purchase fails, I need to cancel my other purchases. If I don't, I still owe the zoo for what I have purchased, and I didn't get any money from my customer, because the package failed!

The solution is to use the timer service from the EJB container. I schedule a method in an EJB to analyse my offers/purchases and for any incomplete session (purchase ID), I cancel all three offers and update my records to mark the purchases as "CANCELLED".

I've put this together as a sample app which includes EJB 3.1, Servlet 3.0, Inteceptors, JPA 2.0, the EJB Timer Service, Validation (JSR-303), JMS and JAX-WS, all based on the GlassFish 3 configuration which was blogged at GlassFish 3 In 30 Minutes. The source for this mega sample app can be downloaded here.

Some final quick notes:

1) A web service, and its client cannot be deployed in the same EAR! That makes sense in normal conditions, but for a sample app, where you want your server to call a test WS, it can cause trouble. So the zoo web service is deployed as a simple web project.

2) The Javadocs for the OrchestrationBean provide some more details of the business process.